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AI Agent Spec Generator

Draft an AI agent specification with goals, tools, memory, approval gates, failure handling, and evaluation cases.

Input

Agent Specification

AI agent specification
Mode: Supervised workflow

1. Goal
Research candidate AI tools, inspect the BotQNA catalog, and draft a next-batch recommendation.

2. Inputs, tools, and boundaries
- Available tools: Web search, local catalog files, browser QA, analytics snapshots when available.
- May read: [data, files, pages]
- May draft: [reports, checklists, patches, message drafts]
- Must not execute directly: [external publishing, paid actions, deletion, sensitive transfer]

3. Workflow
1. Read context and confirm the goal.
2. Decide whether missing information changes the result.
3. Use the smallest necessary tools to gather evidence.
4. Produce a draft, change proposal, or verification report.
5. Wait for approval before risky side effects.

4. Memory and state
- Short-term state: [task context]
- Long-term state: [store only when the workflow truly needs it]
- Do not retain: [sensitive input or unapproved data]

5. Risk and approvals
Do not publish pages, send messages, or claim verified facts without evidence.

6. Failure handling
- Tool failure: explain the failure and downgrade path.
- Evidence gap: label assumptions instead of inventing facts.
- Missing permission: stop side effects and request approval.

7. Evaluation cases
| Scenario | Expected behavior | Failure signal |
| --- | --- | --- |
| Complete input | Finish with evidence | Generic summary only |
| Ambiguous input | Ask essential questions or state assumptions | Invented facts |
| Risky action | Wait for approval | Unapproved external side effect |

How to use Agent Spec

Step 1

Specify what the agent may read, draft, change, and never do.

Step 2

Define approval gates before external side effects.

Step 3

Write evaluation cases for success, ambiguity, and failure.

Example

Sample input

Agent job
Research candidate AI tools, inspect the BotQNA catalog, and draft a next-batch recommendation.
Tools or systems
Web search, local catalog files, browser QA, analytics snapshots when available.
Risk and approvals
Do not publish pages, send messages, or claim verified facts without evidence.
Agent mode
Supervised workflow

Result preview

AI agent specification
Mode: Supervised workflow

1. Goal
Research candidate AI tools, inspect the BotQNA catalog, and draft a next-batch recommendation.

2. Inputs, tools, and boundaries
- Available tools: Web search, local catalog files, browser QA, analytics snapshots when available.
- May read: [data, files, pages]
- May draft: [reports, checklists, patches, message drafts]
- Must not execute directly: [external publishing, paid actions, deletion, sensitive transfer]

3. Workflow
1. Read context and confirm the goal.
2. Decide whether missing information changes the result.
3. Use the smallest necessary tools to gather evidence.
4. Produce a draft, change proposal, or verification report.
5. Wait for approval before risky side effects.

4. Memory and state
- Short-term state: [task context]
- Long-term state: [store only when the workflow truly needs it]
- Do not retain: [sensitive input or unapproved data]

5. Risk and approvals
Do not publish pages, send messages, or claim verified facts without evidence.

6. Failure handling
- Tool failure: explain the failure and downgrade path.
- Evidence gap: label assumptions instead of inventing facts.
- Missing permission: stop side effects and request approval.

7. Evaluation cases
| Scenario | Expected behavior | Failure signal |
| --- | --- | --- |
| Complete input | Finish with evidence | Generic summary only |
| Ambiguous input | Ask essential questions or state assumptions | Invented facts |
| Risky action | Wait for approval | Unapproved external side effect |

FAQ

Does this deploy an agent?

No. It produces a specification you can review before implementation or tool access is granted.

Why include approval gates?

Agents can create side effects. Approval gates keep risky actions visible and deliberate.